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Prof. Dr. Lei Fan
Nanjing University of Information Science & Technology, Nanjing 210023, China

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0 forest recovery
0 deforestation
0 Soil moisture
0 Microwave Remote Sensing
0 Vegetation Optical Depth

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Soil moisture
deforestation
Microwave Remote Sensing
Vegetation Optical Depth
degradation

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Journal article
Published: 23 August 2021 in Remote Sensing of Environment
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Long-term and high-quality surface soil moisture (SSM) and root-zone soil moisture (RZSM) data is crucial for understanding the land-atmosphere interactions of the Qinghai-Tibet Plateau (QTP). More than 40% of QTP is covered by permafrost, yet few studies have evaluated the accuracy of SSM and RZSM products derived from microwave satellite, land surface models (LSMs) and reanalysis over that region. This study tries to address this gap by evaluating a range of satellite and reanalysis estimates of SSM and RZSM in the thawed soil overlaying permafrost in the QTP, using in-situ measurements from sixteen stations. Here, seven SSM products were evaluated: Soil Moisture Active Passive L3 (SMAP-L3) and L4 (SMAP-L4), Soil Moisture and Ocean Salinity in version IC (SMOS-IC), Land Parameter Retrieval Model (LPRM) Advanced Microwave Scanning Radiometer 2 (AMSR2), European Space Agency Climate Change Initiative (ESA CCI), Advanced Scatterometer (ASCAT), and the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5-Land). We also evaluated three RZSM products from SMAP-L4, ERA5-Land, and the Noah land surface model driven by Global Land Data Assimilation System (GLDAS-Noah). The assessment was conducted using five statistical metrics, i.e. Pearson correlation coefficient (R), bias, slope, Root Mean Square Error (RMSE), and unbiased RMSE (ubRMSE) between SSM or RZSM products and in-situ measurements. Our results showed that the ESA CCI, SMAP-L4 and SMOS-IC SSM products outperformed the other SSM products, indicated by higher correlation coefficients (R) (with a median R value of 0.63, 0.44 and 0.57, respectively) and lower ubRMSE (with a median ubRMSE value of 0.05, 0.04 and 0.07 m3/m3, respectively). Yet, SSM overestimation was found for all SSM products. This could be partly attributed to ancillary data used in the retrieval (e.g. overestimation of land surface temperature for SMAP-L3) and to the fact that the products (e.g. LPRM) more easily overestimate the in-situ SSM when the soil is very dry. As expected, SMAP-L3 SSM performed better in areas with sparse vegetation than with dense vegetation covers. For RZSM products, SMAP-L4 and GLDAS-Noah (R = 0.66 and 0.44, ubRMSE = 0.03 and 0.02 m3/m3, respectively) performed better than ERA5-Land (R = 0.46; ubRMSE = 0.03 m3/m3). It is also found that all RZSM products were unable to capture the variations of in-situ RZSM during the freezing/thawing period over the permafrost regions of QTP, due to large deviation for the ice-water phase change simulation and the lack of consideration for unfrozen-water migration during freezing processes in the LSMs.

ACS Style

Zanpin Xing; Lei Fan; Lin Zhao; Gabrielle De Lannoy; Frédéric Frappart; Jian Peng; Xiaojun Li; Jiangyuan Zeng; Amen Al-Yaari; Kun Yang; Tianjie Zhao; Jiancheng Shi; Mengjia Wang; Xiangzhuo Liu; Guojie Hu; Yao Xiao; Erji Du; Ren Li; Yongping Qiao; Jianzong Shi; Jianguang Wen; Mingguo Ma; Jean-Pierre Wigneron. A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau. Remote Sensing of Environment 2021, 265, 112666 .

AMA Style

Zanpin Xing, Lei Fan, Lin Zhao, Gabrielle De Lannoy, Frédéric Frappart, Jian Peng, Xiaojun Li, Jiangyuan Zeng, Amen Al-Yaari, Kun Yang, Tianjie Zhao, Jiancheng Shi, Mengjia Wang, Xiangzhuo Liu, Guojie Hu, Yao Xiao, Erji Du, Ren Li, Yongping Qiao, Jianzong Shi, Jianguang Wen, Mingguo Ma, Jean-Pierre Wigneron. A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau. Remote Sensing of Environment. 2021; 265 ():112666.

Chicago/Turabian Style

Zanpin Xing; Lei Fan; Lin Zhao; Gabrielle De Lannoy; Frédéric Frappart; Jian Peng; Xiaojun Li; Jiangyuan Zeng; Amen Al-Yaari; Kun Yang; Tianjie Zhao; Jiancheng Shi; Mengjia Wang; Xiangzhuo Liu; Guojie Hu; Yao Xiao; Erji Du; Ren Li; Yongping Qiao; Jianzong Shi; Jianguang Wen; Mingguo Ma; Jean-Pierre Wigneron. 2021. "A first assessment of satellite and reanalysis estimates of surface and root-zone soil moisture over the permafrost region of Qinghai-Tibet Plateau." Remote Sensing of Environment 265, no. : 112666.

Journal article
Published: 01 August 2021 in The Innovation
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ACS Style

Xueqin Yang; Jianping Wu; Xiuzhi Chen; Philippe Ciais; Fabienne Maignan; Wenping Yuan; Shilong Piao; Song Yang; Fanxi Gong; Yongxian Su; Yuhang Dai; Liyang Liu; Haicheng Zhang; Damien Bonal; Hui Liu; Guixing Chen; Haibo Lu; Shengbiao Wu; Lei Fan; Pierre Gentine; S. Joseph Wright‬. A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen, broadleaved tropical and subtropical forests. The Innovation 2021, 1 .

AMA Style

Xueqin Yang, Jianping Wu, Xiuzhi Chen, Philippe Ciais, Fabienne Maignan, Wenping Yuan, Shilong Piao, Song Yang, Fanxi Gong, Yongxian Su, Yuhang Dai, Liyang Liu, Haicheng Zhang, Damien Bonal, Hui Liu, Guixing Chen, Haibo Lu, Shengbiao Wu, Lei Fan, Pierre Gentine, S. Joseph Wright‬. A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen, broadleaved tropical and subtropical forests. The Innovation. 2021; ():1.

Chicago/Turabian Style

Xueqin Yang; Jianping Wu; Xiuzhi Chen; Philippe Ciais; Fabienne Maignan; Wenping Yuan; Shilong Piao; Song Yang; Fanxi Gong; Yongxian Su; Yuhang Dai; Liyang Liu; Haicheng Zhang; Damien Bonal; Hui Liu; Guixing Chen; Haibo Lu; Shengbiao Wu; Lei Fan; Pierre Gentine; S. Joseph Wright‬. 2021. "A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen, broadleaved tropical and subtropical forests." The Innovation , no. : 1.

Journal article
Published: 23 July 2021 in Remote Sensing
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Mapping the spatial variation of forest aboveground biomass (AGB) at the national or regional scale is important for estimating carbon emissions and removals and contributing to global stocktake and balancing the carbon budget. Recently, several gridded forest AGB products have been produced for China by integrating remote sensing data and field measurements, yet significant discrepancies remain among these products in their estimated AGB carbon, varying from 5.04 to 9.81 Pg C. To reduce this uncertainty, here, we first compiled independent, high-quality field measurements of AGB using a systematic and consistent protocol across China from 2011 to 2015. We applied two different approaches, an optimal weighting technique (WT) and a random forest regression method (RF), to develop two observationally constrained hybrid forest AGB products in China by integrating five existing AGB products. The WT method uses a linear combination of the five existing AGB products with weightings that minimize biases with respect to the field measurements, and the RF method uses decision trees to predict a hybrid AGB map by minimizing the bias and variance with respect to the field measurements. The forest AGB stock in China was 7.73 Pg C for the WT estimates and 8.13 Pg C for the RF estimates. Evaluation with the field measurements showed that the two hybrid AGB products had a lower RMSE (29.6 and 24.3 Mg/ha) and bias (−4.6 and −3.8 Mg/ha) than all five participating AGB datasets. Our study demonstrated both the WT and RF methods can be used to harmonize existing AGB maps with field measurements to improve the spatial variability and reduce the uncertainty of carbon stocks. The new spatial AGB maps of China can be used to improve estimates of carbon emissions and removals at the national and subnational scales.

ACS Style

Zhongbing Chang; Sanaa Hobeichi; Ying-Ping Wang; XuLi Tang; Gab Abramowitz; Yang Chen; Nannan Cao; Mengxiao Yu; Huabing Huang; GuoYi Zhou; Genxu Wang; Keping Ma; Sheng Du; Shenggong Li; Shijie Han; Youxin Ma; Jean-Pierre Wigneron; Lei Fan; Sassan Saatchi; Junhua Yan. New Forest Aboveground Biomass Maps of China Integrating Multiple Datasets. Remote Sensing 2021, 13, 2892 .

AMA Style

Zhongbing Chang, Sanaa Hobeichi, Ying-Ping Wang, XuLi Tang, Gab Abramowitz, Yang Chen, Nannan Cao, Mengxiao Yu, Huabing Huang, GuoYi Zhou, Genxu Wang, Keping Ma, Sheng Du, Shenggong Li, Shijie Han, Youxin Ma, Jean-Pierre Wigneron, Lei Fan, Sassan Saatchi, Junhua Yan. New Forest Aboveground Biomass Maps of China Integrating Multiple Datasets. Remote Sensing. 2021; 13 (15):2892.

Chicago/Turabian Style

Zhongbing Chang; Sanaa Hobeichi; Ying-Ping Wang; XuLi Tang; Gab Abramowitz; Yang Chen; Nannan Cao; Mengxiao Yu; Huabing Huang; GuoYi Zhou; Genxu Wang; Keping Ma; Sheng Du; Shenggong Li; Shijie Han; Youxin Ma; Jean-Pierre Wigneron; Lei Fan; Sassan Saatchi; Junhua Yan. 2021. "New Forest Aboveground Biomass Maps of China Integrating Multiple Datasets." Remote Sensing 13, no. 15: 2892.

Journal article
Published: 29 April 2021 in Nature Climate Change
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Spatial–temporal dynamics of aboveground biomass (AGB) and forest area affect the carbon cycle, climate and biodiversity in the Brazilian Amazon. Here we investigate interannual changes in AGB and forest area by analysing satellite-based annual AGB and forest area datasets. We found that the gross forest area loss was larger in 2019 than in 2015, possibly due to recent loosening of forest protection policies. However, the net AGB loss was three times smaller in 2019 than in 2015. During 2010–2019, the Brazilian Amazon had a cumulative gross loss of 4.45 Pg C against a gross gain of 3.78 Pg C, resulting in a net AGB loss of 0.67 Pg C. Forest degradation (73%) contributed three times more to the gross AGB loss than deforestation (27%), given that the areal extent of degradation exceeds that of deforestation. This indicates that forest degradation has become the largest process driving carbon loss and should become a higher policy priority. Carbon loss from forests occurs through deforestation or the degradation of existing forest. The loss of forest area in the Brazilian Amazon was higher in 2019 than following drought and an El Niño event in 2015, yet degradation drove three times more biomass loss than deforestation from 2010 to 2019.

ACS Style

Yuanwei Qin; Xiangming Xiao; Jean-Pierre Wigneron; Philippe Ciais; Martin Brandt; Lei Fan; Xiaojun Li; Sean Crowell; Xiaocui Wu; Russell Doughty; Yao Zhang; Fang Liu; Stephen Sitch; Berrien Moore. Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon. Nature Climate Change 2021, 11, 442 -448.

AMA Style

Yuanwei Qin, Xiangming Xiao, Jean-Pierre Wigneron, Philippe Ciais, Martin Brandt, Lei Fan, Xiaojun Li, Sean Crowell, Xiaocui Wu, Russell Doughty, Yao Zhang, Fang Liu, Stephen Sitch, Berrien Moore. Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon. Nature Climate Change. 2021; 11 (5):442-448.

Chicago/Turabian Style

Yuanwei Qin; Xiangming Xiao; Jean-Pierre Wigneron; Philippe Ciais; Martin Brandt; Lei Fan; Xiaojun Li; Sean Crowell; Xiaocui Wu; Russell Doughty; Yao Zhang; Fang Liu; Stephen Sitch; Berrien Moore. 2021. "Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon." Nature Climate Change 11, no. 5: 442-448.

Review
Published: 08 September 2020 in Remote Sensing
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Vegetation is a key element in the energy, water and carbon balances over the land surfaces and is strongly impacted by climate change and anthropogenic effects. Remotely sensed observations are commonly used for the monitoring of vegetation dynamics and its temporal changes from regional to global scales. Among the different indices derived from Earth observation satellites to study the vegetation, the vegetation optical depth (VOD), which is related to the intensity of extinction effects within the vegetation canopy layer in the microwave domain and which can be derived from both passive and active microwave observations, is increasingly used for monitoring a wide range of ecological vegetation variables. Based on different frequency bands used to derive VOD, from L- to Ka-bands, these variables include, among others, the vegetation water content/status and the above ground biomass. In this review, the theoretical bases of VOD estimates for both the passive and active microwave domains are presented and the global long-term VOD products computed from various groups in the world are described. Then, major findings obtained using VOD are reviewed and the perspectives offered by methodological improvements and by new sensors onboard satellite missions recently launched or to be launched in a close future are presented.

ACS Style

Frédéric Frappart; Jean-Pierre Wigneron; Xiaojun Li; Xiangzhuo Liu; Amen Al-Yaari; Lei Fan; Mengjia Wang; Christophe Moisy; Erwan Le Masson; Zacharie Aoulad Lafkih; Clément Vallé; Bertrand Ygorra; Nicolas Baghdadi. Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review. Remote Sensing 2020, 12, 2915 .

AMA Style

Frédéric Frappart, Jean-Pierre Wigneron, Xiaojun Li, Xiangzhuo Liu, Amen Al-Yaari, Lei Fan, Mengjia Wang, Christophe Moisy, Erwan Le Masson, Zacharie Aoulad Lafkih, Clément Vallé, Bertrand Ygorra, Nicolas Baghdadi. Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review. Remote Sensing. 2020; 12 (18):2915.

Chicago/Turabian Style

Frédéric Frappart; Jean-Pierre Wigneron; Xiaojun Li; Xiangzhuo Liu; Amen Al-Yaari; Lei Fan; Mengjia Wang; Christophe Moisy; Erwan Le Masson; Zacharie Aoulad Lafkih; Clément Vallé; Bertrand Ygorra; Nicolas Baghdadi. 2020. "Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review." Remote Sensing 12, no. 18: 2915.

Research article
Published: 10 June 2020 in Science Advances
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In summer 2018, central and northern Europe were stricken by extreme drought and heat (DH2018). The DH2018 differed from previous events in being preceded by extreme spring warming and brightening, but moderate rainfall deficits, yet registering the fastest transition between wet winter conditions and extreme summer drought. Using 11 vegetation models, we show that spring conditions promoted increased vegetation growth, which, in turn, contributed to fast soil moisture depletion, amplifying the summer drought. We find regional asymmetries in summer ecosystem carbon fluxes: increased (reduced) sink in the northern (southern) areas affected by drought. These asymmetries can be explained by distinct legacy effects of spring growth and of water-use efficiency dynamics mediated by vegetation composition, rather than by distinct ecosystem responses to summer heat/drought. The asymmetries in carbon and water exchanges during spring and summer 2018 suggest that future land-management strategies could influence patterns of summer heat waves and droughts under long-term warming.

ACS Style

A. Bastos; P. Ciais; P. Friedlingstein; S. Sitch; J. Pongratz; L. Fan; J. P. Wigneron; U. Weber; M. Reichstein; Z. Fu; P. Anthoni; A. Arneth; V. Haverd; A. K. Jain; E. Joetzjer; J. Knauer; S. Lienert; T. Loughran; P. C. McGuire; H. Tian; N. Viovy; S. Zaehle. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity. Science Advances 2020, 6, eaba2724 .

AMA Style

A. Bastos, P. Ciais, P. Friedlingstein, S. Sitch, J. Pongratz, L. Fan, J. P. Wigneron, U. Weber, M. Reichstein, Z. Fu, P. Anthoni, A. Arneth, V. Haverd, A. K. Jain, E. Joetzjer, J. Knauer, S. Lienert, T. Loughran, P. C. McGuire, H. Tian, N. Viovy, S. Zaehle. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity. Science Advances. 2020; 6 (24):eaba2724.

Chicago/Turabian Style

A. Bastos; P. Ciais; P. Friedlingstein; S. Sitch; J. Pongratz; L. Fan; J. P. Wigneron; U. Weber; M. Reichstein; Z. Fu; P. Anthoni; A. Arneth; V. Haverd; A. K. Jain; E. Joetzjer; J. Knauer; S. Lienert; T. Loughran; P. C. McGuire; H. Tian; N. Viovy; S. Zaehle. 2020. "Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity." Science Advances 6, no. 24: eaba2724.

Research article
Published: 05 February 2020 in Science Advances
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Severe drought and extreme heat associated with the 2015–2016 El Niño event have led to large carbon emissions from the tropical vegetation to the atmosphere. With the return to normal climatic conditions in 2017, tropical forest aboveground carbon (AGC) stocks are expected to partly recover due to increased productivity, but the intensity and spatial distribution of this recovery are unknown. We used low-frequency microwave satellite data (L-VOD) to feature precise monitoring of AGC changes and show that the AGC recovery of tropical ecosystems was slow and that by the end of 2017, AGC had not reached predrought levels of 2014. From 2014 to 2017, tropical AGC stocks decreased by 1.3 1.2 1.5 Pg C due to persistent AGC losses in Africa ( − 0.9 − 1.1 − 0.8 Pg C) and America ( − 0.5 − 0.6 − 0.4 Pg C). Pantropically, drylands recovered their carbon stocks to pre–El Niño levels, but African and American humid forests did not, suggesting carryover effects from enhanced forest mortality.

ACS Style

Jean-Pierre Wigneron; Lei Fan; Philippe Ciais; Ana Bastos; Martin Brandt; Jérome Chave; Sassan Saatchi; Alessandro Baccini; Rasmus Fensholt. Tropical forests did not recover from the strong 2015–2016 El Niño event. Science Advances 2020, 6, eaay4603 .

AMA Style

Jean-Pierre Wigneron, Lei Fan, Philippe Ciais, Ana Bastos, Martin Brandt, Jérome Chave, Sassan Saatchi, Alessandro Baccini, Rasmus Fensholt. Tropical forests did not recover from the strong 2015–2016 El Niño event. Science Advances. 2020; 6 (6):eaay4603.

Chicago/Turabian Style

Jean-Pierre Wigneron; Lei Fan; Philippe Ciais; Ana Bastos; Martin Brandt; Jérome Chave; Sassan Saatchi; Alessandro Baccini; Rasmus Fensholt. 2020. "Tropical forests did not recover from the strong 2015–2016 El Niño event." Science Advances 6, no. 6: eaay4603.

Journal article
Published: 27 January 2020 in Nature Ecology & Evolution
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Anthropogenic land use and land cover changes (LULCC) have a large impact on the global terrestrial carbon sink, but this effect is not well characterized according to biogeographical region. Here, using state-of-the-art Earth observation data and a dynamic global vegetation model, we estimate the impact of LULCC on the contribution of biomes to the terrestrial carbon sink between 1992 and 2015. Tropical and boreal forests contributed equally, and with the largest share of the mean global terrestrial carbon sink. CO2 fertilization was found to be the main driver increasing the terrestrial carbon sink from 1992 to 2015, but the net effect of all drivers (CO2 fertilization and nitrogen deposition, LULCC and meteorological forcing) caused a reduction and an increase, respectively, in the terrestrial carbon sink for tropical and boreal forests. These diverging trends were not observed when applying a conventional LULCC dataset, but were also evident in satellite passive microwave estimates of aboveground biomass. These datasets thereby converge on the conclusion that LULCC have had a greater impact on tropical forests than previously estimated, causing an increase and decrease of the contributions of boreal and tropical forests, respectively, to the growing terrestrial carbon sink.

ACS Style

Torbern Tagesson; Guy Schurgers; Stéphanie Horion; Philippe Ciais; Feng Tian; Martin Brandt; Anders Ahlström; Jean-Pierre Wigneron; Jonas Ardö; Stefan Olin; Lei Fan; Zhendong Wu; Rasmus Fensholt. Recent divergence in the contributions of tropical and boreal forests to the terrestrial carbon sink. Nature Ecology & Evolution 2020, 4, 202 -209.

AMA Style

Torbern Tagesson, Guy Schurgers, Stéphanie Horion, Philippe Ciais, Feng Tian, Martin Brandt, Anders Ahlström, Jean-Pierre Wigneron, Jonas Ardö, Stefan Olin, Lei Fan, Zhendong Wu, Rasmus Fensholt. Recent divergence in the contributions of tropical and boreal forests to the terrestrial carbon sink. Nature Ecology & Evolution. 2020; 4 (2):202-209.

Chicago/Turabian Style

Torbern Tagesson; Guy Schurgers; Stéphanie Horion; Philippe Ciais; Feng Tian; Martin Brandt; Anders Ahlström; Jean-Pierre Wigneron; Jonas Ardö; Stefan Olin; Lei Fan; Zhendong Wu; Rasmus Fensholt. 2020. "Recent divergence in the contributions of tropical and boreal forests to the terrestrial carbon sink." Nature Ecology & Evolution 4, no. 2: 202-209.

Journal article
Published: 08 January 2020 in Nature Communications
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Land use policies have turned southern China into one of the most intensively managed forest regions in the world, with actions maximizing forest cover on soils with marginal agricultural potential while concurrently increasing livelihoods and mitigating climate change. Based on satellite observations, here we show that diverse land use changes in southern China have increased standing aboveground carbon stocks by 0.11 ± 0.05 Pg C y−1 during 2002–2017. Most of this regional carbon sink was contributed by newly established forests (32%), while forests already existing contributed 24%. Forest growth in harvested forest areas contributed 16% and non-forest areas contributed 28% to the carbon sink, while timber harvest was tripled. Soil moisture declined significantly in 8% of the area. We demonstrate that land management in southern China has been removing an amount of carbon equivalent to 33% of regional fossil CO2 emissions during the last 6 years, but forest growth saturation, land competition for food production and soil-water depletion challenge the longevity of this carbon sink service.

ACS Style

Xiaowei Tong; Martin Brandt; Yuemin Yue; Philippe Ciais; Martin Rudbeck Jepsen; Josep Penuelas; Jean-Pierre Wigneron; Xiangming Xiao; Xiao-Peng Song; Stephanie Horion; Kjeld Rasmussen; Sassan Saatchi; Lei Fan; Kelin Wang; Bing Zhang; Zhengchao Chen; Yuhang Wang; Xiaojun Li; Rasmus Fensholt. Forest management in southern China generates short term extensive carbon sequestration. Nature Communications 2020, 11, 1 -10.

AMA Style

Xiaowei Tong, Martin Brandt, Yuemin Yue, Philippe Ciais, Martin Rudbeck Jepsen, Josep Penuelas, Jean-Pierre Wigneron, Xiangming Xiao, Xiao-Peng Song, Stephanie Horion, Kjeld Rasmussen, Sassan Saatchi, Lei Fan, Kelin Wang, Bing Zhang, Zhengchao Chen, Yuhang Wang, Xiaojun Li, Rasmus Fensholt. Forest management in southern China generates short term extensive carbon sequestration. Nature Communications. 2020; 11 (1):1-10.

Chicago/Turabian Style

Xiaowei Tong; Martin Brandt; Yuemin Yue; Philippe Ciais; Martin Rudbeck Jepsen; Josep Penuelas; Jean-Pierre Wigneron; Xiangming Xiao; Xiao-Peng Song; Stephanie Horion; Kjeld Rasmussen; Sassan Saatchi; Lei Fan; Kelin Wang; Bing Zhang; Zhengchao Chen; Yuhang Wang; Xiaojun Li; Rasmus Fensholt. 2020. "Forest management in southern China generates short term extensive carbon sequestration." Nature Communications 11, no. 1: 1-10.

Journal article
Published: 29 July 2019 in Nature Plants
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Changes in terrestrial tropical carbon stocks have an important role in the global carbon budget. However, current observational tools do not allow accurate and large-scale monitoring of the spatial distribution and dynamics of carbon stocks1. Here, we used low-frequency L-band passive microwave observations to compute a direct and spatially explicit quantification of annual aboveground carbon (AGC) fluxes and show that the tropical net AGC budget was approximately in balance during 2010 to 2017, the net budget being composed of gross losses of -2.86 PgC yr-1 offset by gross gains of -2.97 PgC yr-1 between continents. Large interannual and spatial fluctuations of tropical AGC were quantified during the wet 2011 La Niña year and throughout the extreme dry and warm 2015-2016 El Niño episode. These interannual fluctuations, controlled predominantly by semiarid biomes, were shown to be closely related to independent global atmospheric CO2 growth-rate anomalies (Pearson's r = 0.86), highlighting the pivotal role of tropical AGC in the global carbon budget.

ACS Style

Lei Fan; Jean-Pierre Wigneron; Philippe Ciais; Jérôme Chave; Martin Brandt; Rasmus Fensholt; Sassan S. Saatchi; Ana Bastos; Amen Al-Yaari; Koen Hufkens; Yuanwei Qin; Xiangming Xiao; Chi Chen; Ranga B. Myneni; Roberto Fernandez-Moran; Arnaud Mialon; N. J. Rodriguez-Fernandez; Yann Kerr; Feng Tian; Josep Peñuelas. Satellite-observed pantropical carbon dynamics. Nature Plants 2019, 5, 944 -951.

AMA Style

Lei Fan, Jean-Pierre Wigneron, Philippe Ciais, Jérôme Chave, Martin Brandt, Rasmus Fensholt, Sassan S. Saatchi, Ana Bastos, Amen Al-Yaari, Koen Hufkens, Yuanwei Qin, Xiangming Xiao, Chi Chen, Ranga B. Myneni, Roberto Fernandez-Moran, Arnaud Mialon, N. J. Rodriguez-Fernandez, Yann Kerr, Feng Tian, Josep Peñuelas. Satellite-observed pantropical carbon dynamics. Nature Plants. 2019; 5 (9):944-951.

Chicago/Turabian Style

Lei Fan; Jean-Pierre Wigneron; Philippe Ciais; Jérôme Chave; Martin Brandt; Rasmus Fensholt; Sassan S. Saatchi; Ana Bastos; Amen Al-Yaari; Koen Hufkens; Yuanwei Qin; Xiangming Xiao; Chi Chen; Ranga B. Myneni; Roberto Fernandez-Moran; Arnaud Mialon; N. J. Rodriguez-Fernandez; Yann Kerr; Feng Tian; Josep Peñuelas. 2019. "Satellite-observed pantropical carbon dynamics." Nature Plants 5, no. 9: 944-951.

Journal article
Published: 18 March 2019 in Remote Sensing
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Hydro-agricultural applications often require surface soil moisture (SM) information at high spatial resolutions. In this study, daily spatial patterns of SM at a spatial resolution of 1 km over the Babao River Basin in northwestern China were mapped using a Bayesian-based upscaling algorithm, which upscaled point-scale measurements to the grid-scale (1 km) by retrieving SM information using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived land surface temperature (LST) and topography data (including aspect and elevation data) and in situ measurements from a wireless sensor network (WSN). First, the time series of pixel-scale (1 km) representative SM information was retrieved from in situ measurements of SM, topography data, and LST. Second, Bayesian linear regression was used to calibrate the relationship between the representative SM and the WSN measurements. Last, the calibrated relationship was used to upscale a network of in situ measured SM to map spatially continuous SM at a high resolution. The upscaled SM data were evaluated against ground-based SM measurements with satisfactory accuracy—the overall correlation coefficient (r), slope, and unbiased root mean square difference (ubRMSD) values were 0.82, 0.61, and 0.025 m3/m3, respectively. Moreover, when accounting for topography, the proposed upscaling algorithm outperformed the algorithm based only on SM derived from LST (r = 0.80, slope = 0.31, and ubRMSD = 0.033 m3/m3). Notably, the proposed upscaling algorithm was able to capture the dynamics of SM under extreme dry and wet conditions. In conclusion, the proposed upscaled method can provide accurate high-resolution SM estimates for hydro-agricultural applications.

ACS Style

Lei Fan; A. Al-Yaari; Frédéric Frappart; Jennifer J. Swenson; Qing Xiao; Jianguang Wen; Rui Jin; Jian Kang; Xiaojun Li; R. Fernandez-Moran; J.-P. Wigneron. Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures. Remote Sensing 2019, 11, 656 .

AMA Style

Lei Fan, A. Al-Yaari, Frédéric Frappart, Jennifer J. Swenson, Qing Xiao, Jianguang Wen, Rui Jin, Jian Kang, Xiaojun Li, R. Fernandez-Moran, J.-P. Wigneron. Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures. Remote Sensing. 2019; 11 (6):656.

Chicago/Turabian Style

Lei Fan; A. Al-Yaari; Frédéric Frappart; Jennifer J. Swenson; Qing Xiao; Jianguang Wen; Rui Jin; Jian Kang; Xiaojun Li; R. Fernandez-Moran; J.-P. Wigneron. 2019. "Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures." Remote Sensing 11, no. 6: 656.

Journal article
Published: 21 February 2019 in Remote Sensing of Environment
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Soil moisture (SM) is a key state variable in understanding the climate system through its control on the land surface energy, water budget partitioning, and the carbon cycle. Monitoring SM at regional scale has become possible thanks to microwave remote sensing. In the past two decades, several satellites were launched carrying on board either radiometer (passive) or radar (active) or both sensors in different frequency bands with various spatial and temporal resolutions. Soil moisture algorithms are in rapid development and their improvements/revisions are ongoing. The latest SM retrieval products and versions of products that have been recently released are not yet, to our knowledge, comprehensively evaluated and inter-compared over different ecoregions and climate conditions. The aim of this paper is to comprehensively evaluate the most recent microwave-based SM retrieval products available from NASA's (National Aeronautics and Space Administration) SMAP (Soil Moisture Active Passive) satellite, ESA's led mission (European Space Agency) SMOS (Soil Moisture and Ocean Salinity) satellite, ASCAT (Advanced Scatterometer) sensor on board the meteorological operational (Metop) platforms Metop-A and Metop-B, and the ESA Climate Change Initiative (CCI) blended long-term SM time series. More specifically, in this study we compared SMAPL3 V4, SMOSL3 V300, SMOSL2 V650, ASCAT H111, and CCI V04.2 and the new SMOS-IC (V105) SM product. This evaluation was achieved using four statistical scores: Pearson correlation (considering both original observations and anomalies), RMSE, unbiased RMSE, and Bias between remotely-sensed SM retrievals and ground-based measurements from >1000 stations from 17 monitoring networks, spread over the globe, disseminated through the International Soil Moisture Network (ISMN). The analysis reveals that the performance of the remotely-sensed SM retrievals generally varies depending on ecoregions, land cover types, climate conditions, and between the monitoring networks. It also reveals that temporal sampling of the data, the frequency of data in time and the spatial coverage, affect the performance metrics. Overall, the performance of SMAP and SMOS-IC products compared slightly better with respect to the ISMN in situ observations than the other remotely-sensed products.

ACS Style

A. Al-Yaari; Jean-Pierre Wigneron; Wouter Dorigo; A. Colliander; T. Pellarin; S. Hahn; A. Mialon; P. Richaume; Roberto Fernandez Moran; Lei Fan; Y.H. Kerr; G. De Lannoy. Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements. Remote Sensing of Environment 2019, 224, 289 -303.

AMA Style

A. Al-Yaari, Jean-Pierre Wigneron, Wouter Dorigo, A. Colliander, T. Pellarin, S. Hahn, A. Mialon, P. Richaume, Roberto Fernandez Moran, Lei Fan, Y.H. Kerr, G. De Lannoy. Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements. Remote Sensing of Environment. 2019; 224 ():289-303.

Chicago/Turabian Style

A. Al-Yaari; Jean-Pierre Wigneron; Wouter Dorigo; A. Colliander; T. Pellarin; S. Hahn; A. Mialon; P. Richaume; Roberto Fernandez Moran; Lei Fan; Y.H. Kerr; G. De Lannoy. 2019. "Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements." Remote Sensing of Environment 224, no. : 289-303.

Journal article
Published: 09 April 2018 in Nature Ecology & Evolution
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The African continent is facing one of the driest periods in the past three decades as well as continued deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for improved capabilities of monitoring large-scale aboveground carbon stock dynamics. Here we use a satellite dataset based on vegetation optical depth derived from low-frequency passive microwaves (L-VOD) to quantify annual aboveground biomass-carbon changes in sub-Saharan Africa between 2010 and 2016. L-VOD is shown not to saturate over densely vegetated areas. The overall net change in drylands (53% of the land area) was −0.05 petagrams of C per year (Pg C yr−1) associated with drying trends, and a net change of −0.02 Pg C yr−1 was observed in humid areas. These trends reflect a high inter-annual variability with a very dry year in 2015 (net change, −0.69 Pg C) with about half of the gross losses occurring in drylands. This study demonstrates, first, the applicability of L-VOD to monitor the dynamics of carbon loss and gain due to weather variations, and second, the importance of the highly dynamic and vulnerable carbon pool of dryland savannahs for the global carbon balance, despite the relatively low carbon stock per unit area.

ACS Style

Martin Brandt; Jean-Pierre Wigneron; Jerome Chave; Torbern Tagesson; Josep Penuelas; Philippe Ciais; Kjeld Rasmussen; Feng Tian; Cheikh Mbow; Amen Al-Yaari; Nemesio Rodriguez-Fernandez; Guy Schurgers; Wenmin Zhang; Jinfeng Chang; Yann Kerr; Aleixandre Verger; Compton Tucker; Arnaud Mialon; Laura Vang Rasmussen; Lei Fan; Rasmus Fensholt. Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands. Nature Ecology & Evolution 2018, 2, 827 -835.

AMA Style

Martin Brandt, Jean-Pierre Wigneron, Jerome Chave, Torbern Tagesson, Josep Penuelas, Philippe Ciais, Kjeld Rasmussen, Feng Tian, Cheikh Mbow, Amen Al-Yaari, Nemesio Rodriguez-Fernandez, Guy Schurgers, Wenmin Zhang, Jinfeng Chang, Yann Kerr, Aleixandre Verger, Compton Tucker, Arnaud Mialon, Laura Vang Rasmussen, Lei Fan, Rasmus Fensholt. Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands. Nature Ecology & Evolution. 2018; 2 (5):827-835.

Chicago/Turabian Style

Martin Brandt; Jean-Pierre Wigneron; Jerome Chave; Torbern Tagesson; Josep Penuelas; Philippe Ciais; Kjeld Rasmussen; Feng Tian; Cheikh Mbow; Amen Al-Yaari; Nemesio Rodriguez-Fernandez; Guy Schurgers; Wenmin Zhang; Jinfeng Chang; Yann Kerr; Aleixandre Verger; Compton Tucker; Arnaud Mialon; Laura Vang Rasmussen; Lei Fan; Rasmus Fensholt. 2018. "Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands." Nature Ecology & Evolution 2, no. 5: 827-835.

Journal article
Published: 01 February 2018 in Remote Sensing of Environment
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ACS Style

Lei Fan; Jean-Pierre Wigneron; Qing Xiao; A. Al-Yaari; Jianguang Wen; Nicolas Martin-StPaul; J.-L. Dupuy; François Pimont; A. Al Bitar; Roberto Fernandez Moran; Y.H. Kerr. Evaluation of microwave remote sensing for monitoring live fuel moisture content in the Mediterranean region. Remote Sensing of Environment 2018, 205, 210 -223.

AMA Style

Lei Fan, Jean-Pierre Wigneron, Qing Xiao, A. Al-Yaari, Jianguang Wen, Nicolas Martin-StPaul, J.-L. Dupuy, François Pimont, A. Al Bitar, Roberto Fernandez Moran, Y.H. Kerr. Evaluation of microwave remote sensing for monitoring live fuel moisture content in the Mediterranean region. Remote Sensing of Environment. 2018; 205 ():210-223.

Chicago/Turabian Style

Lei Fan; Jean-Pierre Wigneron; Qing Xiao; A. Al-Yaari; Jianguang Wen; Nicolas Martin-StPaul; J.-L. Dupuy; François Pimont; A. Al Bitar; Roberto Fernandez Moran; Y.H. Kerr. 2018. "Evaluation of microwave remote sensing for monitoring live fuel moisture content in the Mediterranean region." Remote Sensing of Environment 205, no. : 210-223.

Journal article
Published: 09 October 2015 in Remote Sensing
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High spatial resolution soil moisture (SM) data are crucial in agricultural applications, river-basin management, and understanding hydrological processes. Merging multi-resource observations is one of the ways to improve the accuracy of high spatial resolution SM data in the heterogeneous cropland. In this paper, the Bayesian Maximum Entropy (BME) methodology is implemented to merge the following four types of observed data to obtain the spatial distribution of SM at 100 m scale: soil moisture observed by wireless sensor network (WSN), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-derived soil evaporative efficiency (SEE), irrigation statistics, and Polarimetric L-band Multi-beam Radiometer (PLMR)-derived SM products (~700 m). From the poor BME predictions obtained by merging only WSN and SEE data, we observed that the SM heterogeneity caused by irrigation and the attenuating sensitivity of the SEE data to SM caused by the canopies result in BME prediction errors. By adding irrigation statistics to the merged datasets, the overall RMSD of the BME predictions during the low-vegetated periods can be successively reduced from 0.052 m3·m−3to 0.033 m3·m−3. The coefficient of determination (R2) and slope between the predicted and in situ measured SM data increased from 0.32 to 0.64 and from 0.38 to 0.82, respectively, but large estimation errors occurred during the moderately vegetated periods (RMSD = 0.041 m3·m−3, R = 0.43 and the slope = 0.41). Further adding the downscaled SM information from PLMR SM products to the merged datasets, the predictions were satisfactorily accurate with an RMSD of 0.034 m3·m−3, R2 of 0.4 and a slope of 0.69 during moderately vegetated periods. Overall, the results demonstrated that merging multi-resource observations into SM estimations can yield improved accuracy in heterogeneous cropland.

ACS Style

Lei Fan; Qing Xiao; Jianguang Wen; Qiang Liu; Rui Jin; Dongqing You; Xiaowen Li. Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations. Remote Sensing 2015, 7, 13273 -13297.

AMA Style

Lei Fan, Qing Xiao, Jianguang Wen, Qiang Liu, Rui Jin, Dongqing You, Xiaowen Li. Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations. Remote Sensing. 2015; 7 (10):13273-13297.

Chicago/Turabian Style

Lei Fan; Qing Xiao; Jianguang Wen; Qiang Liu; Rui Jin; Dongqing You; Xiaowen Li. 2015. "Mapping High-Resolution Soil Moisture over Heterogeneous Cropland Using Multi-Resource Remote Sensing and Ground Observations." Remote Sensing 7, no. 10: 13273-13297.

Journal article
Published: 18 March 2015 in Remote Sensing
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High spatial resolution airborne data with little sub-pixel heterogeneity were used to evaluate the suitability of the temperature/vegetation (Ts/VI) space method developed from satellite observations, and were explored to improve the performance of the Ts/VI space method for estimating soil moisture (SM). An evaluation of the airborne ΔTs/Fr space (incorporated with air temperature) revealed that normalized difference vegetation index (NDVI) saturation and disturbed pixels were hindering the appropriate construction of the space. The non-disturbed ΔTs/Fr space, which was modified by adjusting the NDVI saturation and eliminating the disturbed pixels, was clearly correlated with the measured SM. The SM estimations of the non-disturbed ΔTs/Fr space using the evaporative fraction (EF) and temperature vegetation dryness index (TVDI) were validated by using the SM measured at a depth of 4 cm, which was determined according to the land surface types. The validation results show that the EF approach provides superior estimates with a lower RMSE (0.023 m3·m−3) value and a higher correlation coefficient (0.68) than the TVDI. The application of the airborne ΔTs/Fr space shows that the two modifications proposed in this study strengthen the link between the ΔTs/Fr space and SM, which is important for improving the precision of the remote sensing Ts/VI space method for monitoring SM.

ACS Style

Lei Fan; Qing Xiao; Jianguang Wen; Qiang Liu; Yong Tang; DongQin You; Heshun Wang; Zhaoning Gong; Xiaowen Li. Evaluation of the Airborne CASI/TASI Ts-VI Space Method for Estimating Near-Surface Soil Moisture. Remote Sensing 2015, 7, 3114 -3137.

AMA Style

Lei Fan, Qing Xiao, Jianguang Wen, Qiang Liu, Yong Tang, DongQin You, Heshun Wang, Zhaoning Gong, Xiaowen Li. Evaluation of the Airborne CASI/TASI Ts-VI Space Method for Estimating Near-Surface Soil Moisture. Remote Sensing. 2015; 7 (3):3114-3137.

Chicago/Turabian Style

Lei Fan; Qing Xiao; Jianguang Wen; Qiang Liu; Yong Tang; DongQin You; Heshun Wang; Zhaoning Gong; Xiaowen Li. 2015. "Evaluation of the Airborne CASI/TASI Ts-VI Space Method for Estimating Near-Surface Soil Moisture." Remote Sensing 7, no. 3: 3114-3137.